By William Murphy from Dublin, Ireland - Met Éireann (Irish Meteorological Service), CC BY-SA 2.0, https://commons.wikimedia.org/w/index.php?curid=3302075
18 in person
18 online
Andrew Singleton [MET Norway]
Alex Deckmyn [RMI]
James Fannon (Met Éireann)
Carlos Peralta (DMI)
Polly Schmederer (GeoSphere Austria)
Samuel Viana (AEMET)
Juanje Gonzalez (AEMET)
5 in person
4 online
Was there anything that was a total game changer for you? (e.g. something you didn’t know before, but will make your work much easier)
Was there anything that was especially bad? (e.g. really badly explained, really boring, really irrelevant)
Any other comments
Installing harp
Setting up a project
Data for the course
read_grid() to read individual files
read_forecast() to read multiple files
harp’s Data Classes
Interpolation to points at read time
Lagged ensembles
Steps in the workflow - RRJV(S/P) 1
read_point_forecast()
read_point_obs()
join_to_fcst()
det/ens_verify()
plot_point_verif()
save_point_verif()
shiny_plot_point_verif()
Steps in the workflow - RRJV(S/P) 1
Observation errors
Grouped verification
Vertical profiles
Conditional verification
It was my first time seeing conditional verification, which will be very useful for analysing performance in specific circumstances
Stratifying verification by wind direction will be especially useful, as long as you know what the direction in degrees means on the compass ;-)
Basic Skeleton
Adding the code
Scaling and observation errors
Non Standard evaluation (NSE)
harp uses NSE for a smoother ride for interactive running
Causes problems for using variables
Embracing variables with {{ }}
Basic Skeleton
Adding the code
Scaling and observation errors
Non Standard evaluation (NSE)
Defining parameters
Looping over parameters with for loops
Functional programming with walk()
harp scripts for UWC-West, ACCORD and DEODE
‘Build a Script’ was particularly useful as I am not an R expert and the good practises discussed here were very useful
Managed to code the basics script for point verification for a new task at our institute during the session on point verification
Workflow for spatial verification
Choosing a verification grid
Neighbourhood Contingency Tables
HIRA
Point verification like workflow for Ensemble FSS
Using dFSS for upscaling probabilistic forecasts
Spatial verification was something that I had not worked within HARP of course, so it was useful to identify ways it can easily replace some existing tools
It would be great if the spatial part was provided in a tidier manner. It is usually the case that the point verification and data ingestion part is prepared before hand and then the code is posted online every day. This does not happen with the spatial part, and there are always last minute developments that would be committed during the week . Also, using the development version in the course might not be the best practice in my opinion, since this version is changing and the functions might change. Would it not be better to use the current stable version instead?
Basic plotting with plot_field() and plot_domain()
Where to find colour palettes
Using ggplot() with geom_geomraster()
Faceting and formatting titles
Tricks for improving plotting speed
geom_georaster()ggplot geom for plotting georeferenced rasters
geom_georaster()map <- get_map(precip_1h$fcst)
ggplot() +
geom_polygon(aes(x, y, group = group), data = map, fill = "grey") +
geom_georaster(
aes(geofield = fcst), data = precip_1h,
upscale_method = "downsample", upscale_factor = 4
) +
geom_polygon(
aes(x, y, group = group), data = map,
fill = "transparent", colour = "grey20"
) +
scale_fill_scico(
"mm", palette = "oslo", trans = "log", direction = -1,
limits = c(0.125, 64), breaks = seq_double(0.125, 10),
na.value = "transparent"
) +
facet_wrap(~member, nrow = 2) +
coord_equal(expand = FALSE) +
theme_harp_map()geom_georaster()The spatial data handling in harp was very impressive and I’ll be using it much more for visualisation going forward
[Good] Getting more familiar with the visualization capabilities of harp
Comments
The parameter handling and scaling (e.g. converting temperature from Kelvin to °C) is much easier now
Being able to get wind speed and direction from U and V is really helpful